ArticleCancer2014
Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research.
Article in Cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed, 58 citations in OpenAlex.
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- Fragmentation of Care in Pancreatic Cancer: Effects on Receipt of Care and Survival.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2022Article
- Fragmentation of care and colorectal cancer survival in South Korea: comparisons according to treatment at multiple hospitals.Journal of cancer research and clinical oncology · 2022Article
- Limited English Proficiency and Disparities in Health Care Engagement Among Patients With Breast Cancer.JCO oncology practice · 2021Article
- Benchmark Method for Cost Computations Across Health Care Systems: Cost of Care per Patient per Day in Breast Cancer Care.JCO oncology practice · 2021Article
- Fragmentation of Care Among Black Women With Breast Cancer and Comorbidities: The Role of Health Systems.JCO oncology practice · 2021Article
- Development and Use of Natural Language Processing for Identification of Distant Cancer Recurrence and Sites of Distant Recurrence Using Unstructured Electronic Health Record Data.JCO clinical cancer informatics · 2021Article
- Population-Based Registry Linkages to Improve Validity of Electronic Health Record-Based Cancer Research.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundUnderstanding of cancer outcomes is limited by data fragmentation. In the current study, the authors analyzed the information yielded by integrating breast cancer data from 3 sources: electronic medical records (EMRs) from 2 health care systems and the state registry.
methodsDiagnostic test and treatment data were extracted from the EMRs of all patients with breast cancer treated between 2000 and 2010 in 2 independent California institutions: a community-based practice (Palo Alto Medical Foundation; "Community") and an academic medical center (Stanford University; "University"). The authors incorporated records from the population-based California Cancer Registry and then linked EMR-California Cancer Registry data sets of Community and University patients.
resultsThe authors initially identified 8210 University patients and 5770 Community patients; linked data sets revealed a 16% patient overlap, yielding 12,109 unique patients. The percentage of all Community patients, but not University patients, treated at both institutions increased with worsening cancer prognostic factors. Before linking the data sets, Community patients appeared to receive less intervention than University patients (mastectomy: 37.6% vs 43.2%; chemotherapy: 35% vs 41.7%; magnetic resonance imaging: 10% vs 29.3%; and genetic testing: 2.5% vs 9.2%). Linked Community and University data sets revealed that patients treated at both institutions received substantially more interventions (mastectomy: 55.8%; chemotherapy: 47.2%; magnetic resonance imaging: 38.9%; and genetic testing: 10.9% [P < .001 for each 3-way institutional comparison]).
conclusionsData linkage identified 16% of patients who were treated in 2 health care systems and who, despite comparable prognostic factors, received far more intensive treatment than others. By integrating complementary data from EMRs and population-based registries, a more comprehensive understanding of breast cancer care and factors that drive treatment use was obtained.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.